29 results
(View BibTeX file of all listed publications)

**Robot Learning for Muscular Robots**
Technical University Darmstadt, Germany, December 2019 (phdthesis)

**Real Time Probabilistic Models for Robot Trajectories**
Technical University Darmstadt, Germany, December 2019 (phdthesis)

**Learning Transferable Representations**
University of Cambridge, UK, 2019 (phdthesis)

**Sample-efficient deep reinforcement learning for continuous control**
University of Cambridge, UK, 2019 (phdthesis)

**Formally justified and modular Bayesian inference for probabilistic programs**
University of Cambridge, UK, 2019 (phdthesis)

**Spatial Filtering based on Riemannian Manifold for Brain-Computer Interfacing**
Technical University of Munich, Germany, 2019 (mastersthesis)

**Pragmatism and Variable Transformations in Causal Modelling**
ETH Zurich, 2019 (phdthesis)

**Quantification of tumor heterogeneity using PET/MRI and machine learning**
Eberhard Karls Universität Tübingen, Germany, 2019 (phdthesis)

**Advances in Probabilistic Modelling: Sparse Gaussian Processes, Autoencoders, and Few-shot Learning**
University of Cambridge, UK, 2019 (phdthesis)

**Nonlinear functional causal models for distinguishing cause from effect**
In *Statistics and Causality: Methods for Applied Empirical Research*, pages: 185-201, 8, 1st, (Editors: Wolfgang Wiedermann and Alexander von Eye), John Wiley & Sons, Inc., 2016 (inbook)

**Advances in computational imaging: Benchmarking Deblurring Algorithms, Deep Neural Inpainting, Depth Estimation from Light Fields**
Eberhard Karls Universität Tübingen, Germany, 2016 (phdthesis)

**A cognitive brain–computer interface for patients with amyotrophic lateral sclerosis**
In *Brain-Computer Interfaces: Lab Experiments to Real-World Applications*, 228(Supplement C):221-239, 8, Progress in Brain Research, (Editors: Damien Coyle), Elsevier, 2016 (incollection)

**Tractable Structured Prediction using the Permutohedral Lattice**
ETH Zurich, 2016 (phdthesis)

**Projected Newton-type methods in machine learning**
In *Optimization for Machine Learning*, pages: 305-330, (Editors: Sra, S., Nowozin, S. and Wright, S. J.), MIT Press, Cambridge, MA, USA, December 2011 (inbook)

**Statistical Learning Theory: Models, Concepts, and Results**
In *Handbook of the History of Logic, Vol. 10: Inductive Logic*, 10, pages: 651-706, (Editors: Gabbay, D. M., Hartmann, S. and Woods, J. H.), Elsevier North Holland, Amsterdam, Netherlands, May 2011 (inbook)

**Crowdsourcing for optimisation of deconvolution methods via an iPhone application**
Hochschule Reutlingen, Germany, April 2011 (mastersthesis)

**Learning functions with kernel methods**
University of Pavia, Italy, January 2011 (phdthesis)

**Robot Learning**
In *Encyclopedia of Machine Learning*, pages: 865-869, Encyclopedia of machine learning, (Editors: Sammut, C. and Webb, G. I.), Springer, New York, NY, USA, January 2011 (inbook)

**What You Expect Is What You Get? Potential Use of Contingent Negative Variation for Passive BCI Systems in Gaze-Based HCI**
In *Affective Computing and Intelligent Interaction*, 6975, pages: 447-456, Lecture Notes in Computer Science, (Editors: D’Mello, S., Graesser, A., Schuller, B. and Martin, J.-C.), Springer, Berlin, Germany, 2011 (inbook)

**Kernel Methods in Bioinformatics **
In *Handbook of Statistical Bioinformatics*, pages: 317-334, Springer Handbooks of Computational Statistics ; 3, (Editors: Lu, H.H.-S., Schölkopf, B. and Zhao, H.), Springer, Berlin, Germany, 2011 (inbook)

**Cue Combination: Beyond Optimality**
In *Sensory Cue Integration*, pages: 144-152, (Editors: Trommershäuser, J., Körding, K. and Landy, M. S.), Oxford University Press, 2011 (inbook)

**Model Learning in Robot Control**
Albert-Ludwigs-Universität Freiburg, Germany, 2011 (phdthesis)

**Nonlinear Multivariate Analysis with Geodesic Kernels**
Biologische Kybernetik, Technische Universität Berlin, February 2002 (diplomathesis)

**Concentration Inequalities and Empirical Processes Theory Applied to the Analysis of Learning Algorithms**
Biologische Kybernetik, Ecole Polytechnique, 2002 (phdthesis) Accepted

**Support Vector Machines: Induction Principle, Adaptive Tuning and Prior Knowledge**
Biologische Kybernetik, 2002 (phdthesis)

**Eine beweistheoretische Anwendung der **
Biologische Kybernetik, Westfälische Wilhelms-Universität Münster, Münster, May 1998 (diplomathesis)

**Qualitative Modeling for Data Miner‘s Requirement**
Biologische Kybernetik, Hong-Ik University, Seoul, Korea, February 1998, Written in Korean (diplomathesis)

**Support Vector Machines for Image Classification**
Biologische Kybernetik, Ecole Normale Superieure de Lyon, 1998 (diplomathesis)

**Support-Vektor-Lernen**
In *Ausgezeichnete Informatikdissertationen 1997*, pages: 135-150, (Editors: G Hotz and H Fiedler and P Gorny and W Grass and S Hölldobler and IO Kerner and R Reischuk), Teubner Verlag, Stuttgart, 1998 (inbook)